IntegrationsEmployment HeroTimescaleDB
Employment Hero + TimescaleDB

Connect Employment Hero and TimescaleDB to Build Intelligent Automations

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Employment Hero

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TimescaleDB

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Frequently Asked Questions

How do I start an integration between Employment Hero and TimescaleDB?

To start, connect both your Employment Hero and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Employment Hero triggers actions in TimescaleDB (or vice versa).

Can we customize how data from Employment Hero is recorded in TimescaleDB?

Absolutely. You can customize how Employment Hero data is recorded in TimescaleDB. This includes choosing which data fields go into which fields of TimescaleDB, setting up custom formats, and filtering out unwanted information.

How often does the data sync between Employment Hero and TimescaleDB?

The data sync between Employment Hero and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Employment Hero to TimescaleDB?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Employment Hero and TimescaleDB?

Yes, you can set conditional logic to control the flow of data between Employment Hero and TimescaleDB. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

Employment Hero

About Employment Hero

Employment Hero is a comprehensive platform designed to streamline HR, payroll, and employee management processes. It offers tools for recruitment, onboarding, performance management, and compliance, making it easier for businesses to manage their workforce efficiently.

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TimescaleDB

About TimescaleDB

TimescaleDB is a powerful time-series database designed for fast ingest and complex queries, making it ideal for handling time-series data efficiently. It extends PostgreSQL, providing scalability and performance enhancements specifically for time-series workloads.

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